Run by Bangor Business School
20.000 Credits or 10.000 ECTS Credits
Semester 1 & 2
Organiser: Prof John Ashton
Overall aims and purpose
This is a foundation course in business analytical skills which includes statistical methods, data collection and interpretation, probability distributions, hypothesis formulation and testing, correlation and regression analysis. It focuses on developing these skills in Microsoft Excel.
Manipulation of algebraic expressions, collection and presentation of data, producing descriptive statistics, measuring uncertainty using probability, estimating confidence intervals, hypothesis testing and investigating association and causality.
B- to B+ (60-69%): Very good performance Most of the relevant information accurately deployed. Good grasp of theoretical/conceptual/practical elements. Good integration of theory/practice/information in pursuit of the assessed work's objectives. Evidence of the use of creative and reflective skills.
A- to A+ (70%+): Outstanding performance. The relevant information accurately deployed. Excellent grasp of theoretical/conceptual/practice elements. Good integration of theory/practice/information in pursuit of the assessed work's objectives. Strong evidence of the use of creative and reflective skills.
C- to C+
C- to C+ (50-59%): Much of the relevant information and skills mostly accurately deployed. Adequate grasp of theoretical/conceptual/practical elements. Fair integration of theory/practice/information in the pursuit of the assessed work's objectives. Some evidence of the use of creative and reflective skills.
D- to D+ (40-49%): No major omissions or inaccuracies in the deployment of information/skills. Some grasp of theoretical/conceptual/practical elements. Integration of theory/practice/information present intermittently in pursuit of the assessed work's objectives.
Apply the methods of statistical inference to formulate and test hypotheses.
Analyse data, and interpret the results.
Derive and manipulate algebraic equations, solve simultaneous linear equations and quadratic equations,
Estimate and specify confidence intervals for a mean and variance.
Investigate patterns of association and causality using correlation and regression analysis.
Describe and summarise data using tables, graphs and measures of central tendency and dispersion.
Evaluate probabilities involving the Binomial, Poisson and Normal distributions.
|S1 Online Tests 1||6.00|
|S! Online Test 2||6.00|
|Semester 1 Exam||32.00|
|Semester 2 Exam||32.00|
|S1 Online test 3||6.00|
|S2 Online test 1||6.00|
|S2 Online Test 2||6.00|
|S2 Online Test 3||6.00|
Teaching and Learning Strategy
One 2-hour lecture per week, which will include practical demonstrations and worked examples to try in class.
Two-hour drop-in workshop every fortnight. 10-hours per semester. This session provides further support for students. Attendance is non-compulsory.
Review and reflect upon the course material and practice the applications of techniques in Excel
- Numeracy - Proficiency in using numbers at appropriate levels of accuracy
- Computer Literacy - Proficiency in using a varied range of computer software
- Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
- Exploring - Able to investigate, research and consider alternatives
- Information retrieval - Able to access different and multiple sources of information
- Inter-personal - Able to question, actively listen, examine given answers and interact sentistevely with others
- Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.
- Self-awareness & Reflectivity - Having an awareness of your own strengths, weaknesses, aims and objectives. Able to regularly review, evaluate and reflect upon the performance of yourself and others
Subject specific skills
- Quantification and design. Data, and their effective organisation, presentation and analysis, are important in economics. The typical student will have some familiarity with the principal sources of economic information and data relevant to industry, commerce, society and government, and have had practice in organising it and presenting it informatively. This skill is important at all stages in the decision-making process.
- Numeracy: the use of quantitative skills to manipulate data, evaluate, estimate and model business problems, functions and phenomena.
Talis Reading listhttp://readinglists.bangor.ac.uk/modules/etb-1114.html
- Curwin, J., Slater, R. and Eadson, D. (2015). Quantitative methods for business decisions, seventh edition. Cengage Learning.
- Newbold, P., Carlson, W.L. and Thorne, B. (2013). Statistics for Business and Economics, 8th ed. Harlow: Pearson.
Courses including this module
Compulsory in courses:
- N325: BSc Finance, Investment & Risk year 1 (BSC/FIR)
- N223: BSc Industrial Management year 1 (BSC/IM)
- L11M: BSc Business Economics (Franchised) year 1 (BSC/PBE)
- N34M: BSc Banking and Finance (Franchised) year 1 (BSC/PBF)
- N82M: BSc International Bus in Tourism & Hospitality (Franchised) year 1 (BSC/PIBTH)
- N83M: BSc Tourism & Hospitality: Managemt Leadership (Franchised) year 1 (BSC/PTHML)